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Proceedings Paper

A robust region-based active contour model with point classification for ultrasound breast lesion segmentation
Author(s): Zhihua Liu; Lidan Zhang; Haibing Ren; Ji-Yeun Kim
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Paper Abstract

Lesion segmentation is one of the key technologies for computer-aided diagnosis (CAD) system. In this paper, we propose a robust region-based active contour model (ACM) with point classification to segment high-variant breast lesion in ultrasound images. First, a local signed pressure force (LSPF) function is proposed to classify the contour points into two classes: local low contrast class and local high contrast class. Secondly, we build a sub-model for each class. For low contrast class, the sub-model is built by combining global energy with local energy model to find a global optimal solution. For high contrast class, the sub-model is just the local energy model for its good level set initialization. Our final energy model is built by adding the two sub-models. Finally, the model is minimized and evolves the level set contour to get the segmentation result. We compare our method with other state-of-art methods on a very large ultrasound database and the result shows that our method can achieve better performance.

Paper Details

Date Published: 28 February 2013
PDF: 8 pages
Proc. SPIE 8670, Medical Imaging 2013: Computer-Aided Diagnosis, 86701P (28 February 2013); doi: 10.1117/12.2006164
Show Author Affiliations
Zhihua Liu, Samsung Advanced Institute of Technology (China)
Lidan Zhang, Samsung Advanced Institute of Technology (China)
Haibing Ren, Samsung Advanced Institute of Technology (China)
Ji-Yeun Kim, Samsung Advanced Institute of Technology (China)


Published in SPIE Proceedings Vol. 8670:
Medical Imaging 2013: Computer-Aided Diagnosis
Carol L. Novak; Stephen Aylward, Editor(s)

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